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Advanced methodology for assessing distribution characteristics of Paris equation coefficients to improve fatigue life prediction

机译:评估巴黎方程系数的分布特性以改善疲劳寿命预测的先进方法

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This paper offers a methodology for coping with information loss following consolidation of data on fatigue crack propagation rates derived from different experiments. It is customary, both in the literature and in standardization, to consolidate results of several experiments conducted under similar conditions, using identical materials. This reduces the ability to implement a probabilistic fracture mechanics approach in order to reliably calculate the distribution of the number of cycles needed to reach a critical value (CV; onset of instability or failure). Such reliable calculation requires, among other things, an estimation of the distribution characteristics of the crack progression curves coefficients represented by models such as Paris or NASGRO, and an estimation of joint distributions of equation coefficients representing such models. Consolidated data reduce the ability to estimate these required distribution characteristics. This work suggests an analytical approach that uses consolidated data, but enables the information to be treated as if it were possible to attribute the data to the various experimental specimens from which they were obtained. Consequently, information required for the evaluation of the distribution of the number of cycles needed to reach a CV can be obtained. The proposed approach is generic and can be applied in additional scientific fields that can benefit from separation of data obtained from different experiments.
机译:本文提供了一种方法,该方法可用于对来自不同实验的疲劳裂纹扩展速率数据进行合并之后的信息丢失处理。无论是在文献中还是在标准化中,习惯上都是使用相同的材​​料来合并在相似条件下进行的几个实验的结果。这降低了实施概率断裂力学方法的能力,以便可靠地计算达到临界值(CV;不稳定或失效的开始)所需的循环次数分布。这种可靠的计算尤其需要估计由诸如Paris或NASGRO之类的模型表示的裂纹扩展曲线系数的分布特性,以及估计代表这种模型的方程系数的联合分布。合并数据会降低估计这些所需分布特征的能力。这项工作提出了一种使用合并数据的分析方法,但可以对信息进行处理,就好像可以将数据归因于从中获取数据的各种实验标本一样。因此,可以获得用于评估达到CV所需的循环数的分布所需的信息。所提出的方法是通用的,可以应用于其他科学领域,这些领域可以受益于分离来自不同实验的数据。

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